Journals / CMC / Vol.59, No.2
Table of Content


  • ARTICLE

    Security and Privacy Frameworks for Access Control Big Data Systems

    Paolina Centonze1,*
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 361-374, 2019, DOI:10.32604/cmc.2019.06223
    Abstract In the security and privacy fields, Access Control (AC) systems are viewed as the fundamental aspects of networking security mechanisms. Enforcing AC becomes even more challenging when researchers and data analysts have to analyze complex and distributed Big Data (BD) processing cluster frameworks, which are adopted to manage yottabyte of unstructured sensitive data. For instance, Big Data systems’ privacy and security restrictions are most likely to failure due to the malformed AC policy configurations. Furthermore, BD systems were initially developed toped to take care of some of the DB issues to address BD challenges and many of these dealt with… More >

  • ARTICLE

    A Data Download Method from RSUs Using Fog Computing in Connected Vehicles

    Dae-Young Kim1, Seokhoon Kim2,*
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 375-387, 2019, DOI:10.32604/cmc.2019.06077
    Abstract Communication is important for providing intelligent services in connected vehicles. Vehicles must be able to communicate with different places and exchange information while driving. For service operation, connected vehicles frequently attempt to download large amounts of data. They can request data downloading to a road side unit (RSU), which provides infrastructure for connected vehicles. The RSU is a data bottleneck in a transportation system because data traffic is concentrated on the RSU. Therefore, it is not appropriate for a connected vehicle to always attempt a high speed download from the RSU. If the mobile network between a connected vehicle and… More >

  • ARTICLE

    Quantitative Analysis of Crime Incidents in Chicago Using Data Analytics Techniques

    Daniel Rivera Ruiz1,*, Alisha Sawant1
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 389-396, 2019, DOI:10.32604/cmc.2019.06433
    Abstract In this paper we aim to identify certain social factors that influence, and thus can be used to predict, the occurrence of crimes. The factors under consideration for this analytic are social demographics such as age, sex, poverty, etc., train ridership, traffic density and the number of business licenses per community area in Chicago, IL. A factor will be considered pertinent if there is high correlation between it and the number of crimes of a particular type in that community area. More >

  • ARTICLE

    A Hierarchical Trust Model for Peer-to-Peer Networks

    Nehal Al-Otaiby1, Heba Kurdi1,*, Shiroq Al-Megren1
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 397-404, 2019, DOI:10.32604/cmc.2019.06236
    Abstract Trust has become an increasingly important issue given society’s growing reliance on electronic transactions. Peer-to-peer (P2P) networks are among the main electronic transaction environments affected by trust issues due to the freedom and anonymity of peers (users) and the inherent openness of these networks. A malicious peer can easily join a P2P network and abuse its peers and resources, resulting in a large-scale failure that might shut down the entire network. Therefore, a plethora of researchers have proposed trust management systems to mitigate the impact of the problem. However, due to the problem’s scale and complexity, more research is necessary.… More >

  • REVIEW

    A Review on Fretting Wear Mechanisms, Models and Numerical Analyses

    Tongyan Yue1,2, Magd Abdel Wahab3,4,*
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 405-432, 2019, DOI:10.32604/cmc.2019.04253
    Abstract Fretting wear is a material damage in contact surfaces due to micro relative displacement between them. It causes some general problems in industrial applications, such as loosening of fasteners or sticking in components supposed to move relative to each other. Fretting wear is a complicated problem involving material properties of tribo-system and working conditions of them. Due to these various factors, researchers have studied the process of fretting wear by experiments and numerical modelling methods. This paper reviews recent literature on the numerical modelling method of fretting wear. After a briefly introduction on the mechanism of fretting wear, numerical models,… More >

  • ARTICLE

    A Deep Collocation Method for the Bending Analysis of Kirchhoff Plate

    Hongwei Guo3, Xiaoying Zhuang3,4,5, Timon Rabczuk1,2,*
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 433-456, 2019, DOI:10.32604/cmc.2019.06660
    Abstract In this paper, a deep collocation method (DCM) for thin plate bending problems is proposed. This method takes advantage of computational graphs and backpropagation algorithms involved in deep learning. Besides, the proposed DCM is based on a feedforward deep neural network (DNN) and differs from most previous applications of deep learning for mechanical problems. First, batches of randomly distributed collocation points are initially generated inside the domain and along the boundaries. A loss function is built with the aim that the governing partial differential equations (PDEs) of Kirchhoff plate bending problems, and the boundary/initial conditions are minimised at those collocation… More >

  • ARTICLE

    Developing a New Security Framework for Bluetooth Low Energy Devices

    Qiaoyang Zhang1, Zhiyao Liang1,*, Zhiping Cai2
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 457-471, 2019, DOI:10.32604/cmc.2019.03758
    Abstract Wearable devices are becoming more popular in our daily life. They are usually used to monitor health status, track fitness data, or even do medical tests, etc. Since the wearable devices can obtain a lot of personal data, their security issues are very important. Motivated by the consideration that the current pairing mechanisms of Bluetooth Low Energy (BLE) are commonly impractical or insecure for many BLE based wearable devices nowadays, we design and implement a security framework in order to protect the communication between these devices. The security framework is a supplement to the Bluetooth pairing mechanisms and is compatible… More >

  • ARTICLE

    Privacy-Preserving Content-Aware Search Based on Two-Level Index

    Zhangjie Fu1,*, Lili Xia1, Yuling Liu2, Zuwei Tian3
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 473-491, 2019, DOI:10.32604/cmc.2019.03785
    Abstract Nowadays, cloud computing is used more and more widely, more and more people prefer to using cloud server to store data. So, how to encrypt the data efficiently is an important problem. The search efficiency of existed search schemes decreases as the index increases. For solving this problem, we build the two-level index. Simultaneously, for improving the semantic information, the central word expansion is combined. The purpose of privacy-preserving content-aware search by using the two-level index (CKESS) is that the first matching is performed by using the extended central words, then calculate the similarity between the trapdoor and the secondary… More >

  • ARTICLE

    A Distributed ADMM Approach for Collaborative Regression Learning in Edge Computing

    Yangyang Li1, Xue Wang2, Weiwei Fang2,*, Feng Xue2, Hao Jin1, Yi Zhang1, Xianwei Li3
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 493-508, 2019, DOI:10.32604/cmc.2019.05178
    Abstract With the recent proliferation of Internet-of-Things (IoT), enormous amount of data are produced by wireless sensors and connected devices at the edge of network. Conventional cloud computing raises serious concerns on communication latency, bandwidth cost, and data privacy. To address these issues, edge computing has been introduced as a new paradigm that allows computation and analysis to be performed in close proximity with data sources. In this paper, we study how to conduct regression analysis when the training samples are kept private at source devices. Specifically, we consider the lasso regression model that has been widely adopted for prediction and… More >

  • ARTICLE

    A Noise-Resistant Superpixel Segmentation Algorithm for Hyperspectral Images

    Peng Fu1,2, Qianqian Xu1, Jieyu Zhang3, Leilei Geng4,*
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 509-515, 2019, DOI:10.32604/cmc.2019.05250
    Abstract The superpixel segmentation has been widely applied in many computer vision and image process applications. In recent years, amount of superpixel segmentation algorithms have been proposed. However, most of the current algorithms are designed for natural images with little noise corrupted. In order to apply the superpixel algorithms to hyperspectral images which are always seriously polluted by noise, we propose a noise-resistant superpixel segmentation (NRSS) algorithm in this paper. In the proposed NRSS, the spectral signatures are first transformed into frequency domain to enhance the noise robustness; then the two widely spectral similarity measures-spectral angle mapper (SAM) and spectral information… More >

  • ARTICLE

    An Influence Maximization Algorithm Based on the Mixed Importance of Nodes

    Yong Hua1, Bolun Chen1,2,*, Yan Yuan1, Guochang Zhu1, Jialin Ma1
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 517-531, 2019, DOI:10.32604/cmc.2019.05278
    Abstract The influence maximization is the problem of finding k seed nodes that maximize the scope of influence in a social network. Therefore, the comprehensive influence of node needs to be considered, when we choose the most influential node set consisted of k seed nodes. On account of the traditional methods used to measure the influence of nodes, such as degree centrality, betweenness centrality and closeness centrality, consider only a single aspect of the influence of node, so the influence measured by traditional methods mentioned above of node is not accurate. In this paper, we obtain the following result through experimental… More >

  • ARTICLE

    Personalized Privacy Protecting Model in Mobile Social Network

    Pingshui Wang1,*, Zecheng Wang1, Tao Chen1,2, Qinjuan Ma1
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 533-546, 2019, DOI:10.32604/cmc.2019.05570
    Abstract With the rapid development of the new generation of information technology, the analysis of mobile social network big data is getting deeper and deeper. At the same time, the risk of privacy disclosure in social network is also very obvious. In this paper, we summarize the main access control model in mobile social network, analyze their contribution and point out their disadvantages. On this basis, a practical privacy policy is defined through authorization model supporting personalized privacy preferences. Experiments have been conducted on synthetic data sets. The result shows that the proposed privacy protecting model could improve the security of… More >

  • ARTICLE

    Dependency-Based Local Attention Approach to Neural Machine Translation

    Jing Qiu1, Yan Liu2, Yuhan Chai2, Yaqi Si2, Shen Su1, ∗, Le Wang1, ∗, Yue Wu3
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 547-562, 2019, DOI:10.32604/cmc.2019.05892
    Abstract Recently dependency information has been used in different ways to improve neural machine translation. For example, add dependency labels to the hidden states of source words. Or the contiguous information of a source word would be found according to the dependency tree and then be learned independently and be added into Neural Machine Translation (NMT) model as a unit in various ways. However, these works are all limited to the use of dependency information to enrich the hidden states of source words. Since many works in Statistical Machine Translation (SMT) and NMT have proven the validity and potential of using… More >

  • ARTICLE

    A HEVC Video Steganalysis Algorithm Based on PU Partition Modes

    Zhonghao Li1, Laijin Meng1, Shutong Xu1, Zhaohong Li1,2,*, Yunqing Shi3, Yuanchang Liang1
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 563-574, 2019, DOI:10.32604/cmc.2019.05565
    Abstract Steganalysis is a technique used for detecting the existence of secret information embedded into cover media such as images and videos. Currently, with the higher speed of the Internet, videos have become a kind of main methods for transferring information. The latest video coding standard High Efficiency Video Coding (HEVC) shows better coding performance compared with the H.264/AVC standard published in the previous time. Therefore, since the HEVC was published, HEVC videos have been widely used as carriers of hidden information.
    In this paper, a steganalysis algorithm is proposed to detect the latest HEVC video steganography method which is based… More >

  • ARTICLE

    Feedback LSTM Network Based on Attention for Image Description Generator

    Zhaowei Qu1,*, Bingyu Cao1, Xiaoru Wang1, Fu Li2, Peirong Xu1, Luhan Zhang1
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 575-589, 2019, DOI:10.32604/cmc.2019.05569
    Abstract Images are complex multimedia data which contain rich semantic information. Most of current image description generator algorithms only generate plain description, with the lack of distinction between primary and secondary object, leading to insufficient high-level semantic and accuracy under public evaluation criteria. The major issue is the lack of effective network on high-level semantic sentences generation, which contains detailed description for motion and state of the principal object. To address the issue, this paper proposes the Attention-based Feedback Long Short-Term Memory Network (AFLN). Based on existing codec framework, there are two independent sub tasks in our method: attention-based feedback LSTM… More >

  • ARTICLE

    Street-Level Landmarks Acquisition Based on SVM Classifiers

    Ruixiang Li1,2, Yingying Liu3, Yaqiong Qiao1,2, Te Ma1,2, Bo Wang4, Xiangyang Luo1,2,*
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 591-606, 2019, DOI:10.32604/cmc.2019.05208
    Abstract High-density street-level reliable landmarks are one of the important foundations for street-level geolocation. However, the existing methods cannot obtain enough street-level landmarks in a short period of time. In this paper, a street-level landmarks acquisition method based on SVM (Support Vector Machine) classifiers is proposed. Firstly, the port detection results of IPs with known services are vectorized, and the vectorization results are used as an input of the SVM training. Then, the kernel function and penalty factor are adjusted for SVM classifiers training, and the optimal SVM classifiers are obtained. After that, the classifier sequence is constructed, and the IPs… More >

  • ARTICLE

    Analysis and Improvement of Steganography Protocol Based on Bell States in Noise Environment

    Zhiguo Qu1,*, Shengyao Wu2, Wenjie Liu1, Xiaojun Wang3
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 607-624, 2019, DOI:10.32604/cmc.2019.02656
    Abstract In the field of quantum communication, quantum steganography is an important branch of quantum information hiding. In a realistic quantum communication system, quantum noises are unavoidable and will seriously impact the safety and reliability of the quantum steganographic system. Therefore, it is very important to analyze the influence of noise on the quantum steganography protocol and how to reduce the effect of noise. This paper takes the quantum steganography protocol proposed in 2010 as an example to analyze the effects of noises on information qubits and secret message qubits in the four primary quantum noise environments. The results show that… More >

  • ARTICLE

    A Multi-Feature Weighting Based K-Means Algorithm for MOOC Learner Classification

    Yuqing Yang1,2, Dequn Zhou1,*, Xiaojiang Yang1,3,4
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 625-633, 2019, DOI:10.32604/cmc.2019.05246
    Abstract Massive open online courses (MOOC) have recently gained worldwide attention in the field of education. The manner of MOOC provides a new option for learning various kinds of knowledge. A mass of data miming algorithms have been proposed to analyze the learner’s characteristics and classify the learners into different groups. However, most current algorithms mainly focus on the final grade of the learners, which may result in an improper classification. To overcome the shortages of the existing algorithms, a novel multi-feature weighting based K-means (MFWK-means) algorithm is proposed in this paper. Correlations between the widely used feature grade and other… More >

  • ARTICLE

    Message Authentication with a New Quantum Hash Function

    Yalan Wang1,2, Yuling Chen1,*, Haseeb Ahmad3, Zhanhong Wei4
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 635-648, 2019, DOI:10.32604/cmc.2019.05251
    Abstract To ensure the security during the communication, we often adopt different ways to encrypt the messages to resist various attacks. However, with the computing power improving, the existing encryption and authentication schemes are being faced with big challenges. We take the message authentication as an example into a careful consideration. Then, we proposed a new message authentication scheme with the Advanced Encryption Standard as the encryption function and the new quantum Hash function as the authentication function. Firstly, the Advanced Encryption Standard algorithm is used to encrypt the result of the initial message cascading the corresponding Hash values, which ensures… More >

  • ARTICLE

    Maximum Data Generation Rate Routing Protocol Based on Data Flow Controlling Technology for Rechargeable Wireless Sensor Networks

    Demin Gao1, 2, *, Shuo Zhang1, Fuquan Zhang1, Xijian Fan1, Jinchi Zhang1,∗
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 649-667, 2019, DOI:10.32604/cmc.2019.05195
    Abstract For rechargeable wireless sensor networks, limited energy storage capacity, dynamic energy supply, low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario. Therefore, before data delivery, a sensor has to update its waking schedule continuously and share them to its neighbors, which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets. In this work, we propose the maximum data generation rate routing protocol based on data flow controlling technology. For a… More >

  • ARTICLE

    Novel Approach for Automatic Region of Interest and Seed Point Detection in CT Images Based on Temporal and Spatial Data

    Zhe Liu1, Charlie Maere1,*, Yuqing Song1
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 669-686, 2019, DOI:10.32604/cmc.2019.04590
    Abstract Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing. We propose a novel approach of automatically identifying region of interest in Computed Tomography Image (CT) images based on temporal and spatial data . Our method is a 3 stages approach, 1) We extract organ features from the CT images by adopting the Hounsfield filter. 2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’ area and automatically detect a seed point. 3) We use a novel approach to track the growing region changes… More >

  • ARTICLE

    Waveband Selection with Equivalent Prediction Performance for FTIR/ATR Spectroscopic Analysis of COD in Sugar Refinery Waste Water

    Jun Xie1, Dapeng Sun1, Jiaxiang Cai2, Fuhong Cai1,*
    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 687-695, 2019, DOI:10.32604/cmc.2019.03658
    Abstract The level of chemical oxygen demand (COD) is an important index to evaluate whether sewage meets the discharge requirements, so corresponding tests should be carried out before discharge. Fourier transform infrared spectroscopy (FTIR) and attenuated total reflectance (ATR) can detect COD in sewage effectively, which has advantages over conventional chemical analysis methods. And the selection of characteristic bands was one of the key links in the application of FTIR/ATR spectroscopy. In this work, based on the moving window partial least-squares (MWPLS) regression to select a characteristic wavelength, a method of equivalent wavelength selection was proposed combining with paired t-test equivalent… More >

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